This book covers sustainable development in smart society's 5.0 using data analytics. The data analytics is the approach of integrating diversified heterogeneous data for predictive analysis to accredit innovation, decision making, business analysis, and strategic decision making. The data science brings together the research in the field of data analytics, online information analytics, and big data analytics to synthesize issues, challenges, and opportunities across smart society 5.0. Accordingly, the book offers an interesting and insightful read for researchers in the areas of decision analytics, cognitive analytics, big data analytics, visual analytics, text analytics, spatial analytics, risk analytics, graph analytics, predictive analytics, and analytics-enabled applications.

This book gives a complete overview of cloud computing: its importance, its trends, innovations, and its amalgamation with other technologies. Key Features: 1. In-depth explanation of emerging technologies utilizing cloud computing 2. Supplemented with visuals, flowcharts, and diagrams 3. Real-time examples included 4. Caters to beginners, as well as advanced researchers, by explaining implications, innovations, issues, and challenges of cloud computing 5. Highlights the need for cloud computing and the true benefits derived by its application and integration in emerging technologies 6. Simple, easy language

Provides an overview of the role engineering plays in climate change and environmental pollution Presents an updated overview of Green Engineering focusing on green technology Innovations Explores energy management strategies Discusses green communication technologies, green computing technologies, green smart buildings, green smart lighting, green smart mobility management, fuel-efficient transportation, paperless offices, energy efficiency measures, waste recycling, etc. Identifies the development of sustainable plans and programs at the urban level within the current legislative framework

Examines the recent research trends and the future of Cyber-Physical systems, IoT, and Autonomous Systems as it relates to Industry 4.0 Investigates various challenges across multiple sectors and different industries Offers a discussion on the recent advancements in Industry 4.0 technological developments for operations and supply chain management Explores the potential for the IoT, Autonomous and Cyber-Physical Systems to replace the current mechanical, people-based systems in various sectors Discusses additional topics such as Machine Learning and Cloud Computing

Explores the potential for disruptive technologies in different industries Addresses the challenges associated with the practical implementation or adoption of disruptive technologies Discusses topics related to IoT, Machine Learning, Sensors, Artificial Intelligence and Cloud Computing for Industry 4.0 and 5.0 Includes examples of the implementation of Industry 4.0 and 5.0 in various sectors, including engineering Contains many case studies for easy comprehension.

The aim of this book is to provide insight into Data Science and Artificial Learning Techniques based on Industry 4.0, conveys how Machine Learning & Data Science are becoming an essential part of industrial and academic research. Varying from healthcare to social networking and everywhere hybrid models for Data Science, Al, and Machine Learning are being used. The book describes different theoretical and practical aspects and highlights how new systems are being developed. Along with focusing on the research trends, challenges and future of AI in Data Science, the book explores the potential for integration of advanced AI algorithms, addresses the challenges of Data Science for Industry 4.0, covers different security issues, includes qualitative and quantitative research, and offers case studies with working models. This book also provides an overview of AI and Data Science algorithms for readers who do not have a strong mathematical background. Undergraduates, postgraduates, academicians, researchers, and industry professionals will benefit from this book and use it as a guide.

This book covers sustainable development in smart society’s 5.0 using data analytics. The data analytics is the approach of integrating diversified heterogeneous data for predictive analysis to accredit innovation, decision making, business analysis, and strategic decision making. The data science brings together the research in the field of data analytics, online information analytics, and big data analytics to synthesize issues, challenges, and opportunities across smart society 5.0. Accordingly, the book offers an interesting and insightful read for researchers in the areas of decision analytics, cognitive analytics, big data analytics, visual analytics, text analytics, spatial analytics, risk analytics, graph analytics, predictive analytics, and analytics-enabled applications.